To increase the bandwidth of a wideband receiver for surveillance applications, an in-phase/quadrature-phase (I/Q) channel-based receiver is a potential approach. However, the image caused by an imperfect coupler prevents the I/Q channel-based receiver from becoming a reality. Air Force Research Laboratory developed an imbalance compensation method covering two Nyquist zones. In this study, the authors present its implementation with a field-programmable gate array board. Experimental results demonstrate the effectiveness of the proposed imbalance compensation algorithm and its feasibility.

Radar sensor is a promising candidate for space surveillance, providing timely assessment of space objects and events. Weak space target tracking is a challenging conundrum mainly because of the low detection probability and poor measurement accuracy. In this study, a novel method of weak space target tracking assisted by strong space target is proposed. By introducing the relative motion tracking, the steady-state estimates of strong target are utilised to improve the state estimation of weak target. Compared with weak target tracking without strong target assistance, the proposed tracking method can provide higher state estimation accuracy, faster convergence rate and better track validity probability for weak target. The results of numerical simulations have validated the effectiveness of the proposed technique.

In this study, an algorithm is presented to eliminate the ambiguity of the wind direction from the monostatic radar. The true wind direction can be obtained by comparing three angles that reflect the differences between wind direction and three adjacent radar beams. The correlation coefficient and the root-mean-square (RMS) error between the inversion data and the anemometer data are 0.67 and 49.8°, respectively. When the data whose wind speed is greater than the threshold 4.67 m/s are used, the correlation coefficient and the RMS error are 0.93 and 24.6°. Therefore, the effect of the wind speed threshold on the radar measurements should be put into consideration in the data processing. The results make clear that the algorithm can remove the ambiguity of the wind direction effectively, and authors can utilise the algorithm to estimate the wind direction.

The receiver and transmitter polarisations (RTPs) have great influence on detection performance in multi-FM-based passive radar. As the transmitter polarisation is uncontrollable in passive radar, the purpose of this study is to determine the appropriate receiver polarisation of the surveillance channel. Firstly, the impact of polarisation on radar detection performance is discussed from three aspects. Then, the probability of detection is used as a metric to select the better RTPs. Theoretical results show that, when most of the transmitted signals in the working band are vertically polarised, the horizontally polarised receiver can obtain better detection performance than the vertically polarised one. Finally, theoretical results are confirmed by field experiments.

A new method for selecting auxiliary channels in reduced-dimension space–time adaptive processing (STAP) based on maximum cross-correlation energy has been proposed for airborne multiple-input multiple-output radar. It is demonstrated that the proposed algorithm can achieve the same output signal-to-interference–noise ratio (SINR) performance as the multistage multiple-beam STAP algorithm which can assure the optimal performance when the number of auxiliary channels is fixed, but the auxiliary channels selecting process of the proposed algorithm is extremely simplified. Hence, the computation complexity is reduced dramatically. Practical considerations dictate that only the minimum number of auxiliary channels [(adaptive degrees of freedom (DoFs)] is required to achieve the desired array performance. The proposed approach can achieve the desired output signal-to-interference–noise performance with the minimum number of auxiliary channels. Consequently, the proposed approach can reduce the requirement of the sample support dramatically. It is demonstrated that the SINR loss will be <3 dB when only one channel is selected as the auxiliary channel. Generally, two to three channels are enough even when the clutter covariance matrix is unknown. This will be more obvious advantage when the number of independent and identically distributed secondary samples is limited. The reduction in DoFs can make the proposed approach more suitable for the practical clutter environments.

In space-time adaptive processing (STAP), the required interference covariance matrix is commonly estimated from homogeneous samples. However, the real interference environments are often heterogeneous, which is induced by the fact that the training samples do not share the same interference property with the cell under test (CUT), and thus the interference covariance matrix estimated from the training samples is mismatched with the real one. To improve the performance of STAP in heterogeneous interference environments, this paper proposes a robust training samples selection algorithm which is based on the spectral similarity of the interference. The spectrums of samples are estimated firstly, which are then utilised to calculate the similarity between the interference of the CUT and those of the training samples. Then, the samples whose interference spectrums are similar to that of the CUT are selected as the final training samples, such that the performance of the interference covariance matrix estimated from these samples can be improved significantly. Besides, to avoid the target self-nulling effect, a simple technique is adopted to exclude the samples which are contaminated by target signal. The proposed method is applied to real radar data, and experimental results demonstrate the effectiveness of the proposed method.

This study presents an automatic method for extracting the jet engine features from the joint time-frequency (JTF) representation of jet engine modulation (JEM) signals. First, empirical mode decomposition with adaptive low-pass filtering was employed to extract the first harmonic component of the JEM signal. Then, a smoothed pseudo Wigner–Ville distribution (SPWVD) technique was used for acquiring the refined JTF representation. After converting the SPWVD result into an image with RGB colours, the green component was extracted as a representative of the JEM component. Finally, the peaks detected from the extracted green component can represent the jet engine features. The approach proposed in this study is significant because the overall procedures for extracting the jet engine features are not manual but automatically performed based on the image processing method. Application to measured JEM signals demonstrated that the automatic feature presented in this study improved the accuracy of JEM analysis and is expected to be efficient for real-time radar non-cooperative target recognition.

New Galileo and enhanced GPS signals use binary offset carrier (BOC) waveforms namely composite BOC (CBOC) and alternate BOC (AltBOC). For good tracking, these signals require precise acquisition. The more sidelobes the autocorrelation function has, the tighter the pull-in range region is, and the more precise the acquisition must be. Further, when multipath propagation is encountered, the received waveform is so distorted that a precise acquisition becomes difficult. To solve this problem, two approaches are considered by enhancing either the acquisition stage or the tracking one. At the acquisition stage, the authors focus on Bayesian estimation where Bernoulli–Gaussian and Laplacian (Lp) priors for channel distribution are compared. On one hand, the BG prior leads to rather complex optimisation criterion that can be solved by a Markov Chain Monte Carlo algorithm. This is a very efficient but time consuming method. On the other hand, the Lp prior results in exact maximum a posteriori calculation. In this case, the Bayesian estimation involves an ℓ₁-norm penalisation and provides quite good performance for reasonable acquisition complexity. At the tracking stage, many works have dealt with false lock positions, such as the sidelobe cancellation method (SCM) or multiple gate delay (MGD) technique. In this article, the authors highlight the need for accurate acquisition for better detection and estimation at the tracking output. The SCM and MGD methods are taken as examples to illustrate this influence. The analysed signals are GPS BPSK(1), BPSK(10), and Galileo CBOC(6, 1, 1/11) and AltBOC(15, 10) modulated open service signals. The impact of multipath is studied for line of sight (LOS) signal, LOS plus multipath replicas, and multipath alone. The authors compare the results of classical acquisition followed by precise tracking to those of Bayesian acquisition followed by classical tracking. The results of Bayesian acquisition followed by precise tracking are also provided.

This study deals with an improvement of radar cross section (RCS) of stealth target model such as F-117A with a higher aspect vision, and proposes a new detection technique based on stratospheric balloon-borne netted radar system. Normally, it is very difficult to statistically model a stealth target by conventional analytically probability density function (pdf) expressions. Thus, a novel non-parametric detection technique using time difference of arrival (TDOA) and physical optics (PO) approximation method is proposed. Finally, Legendre orthogonal polynomials (LOP) using to reconstruct the pdf of stealth RCS predicted by PO. The potential problem of proposed scheme is instability of the platform caused by sudden gusts of winds. The balloon flight control is studied in detail by considering external force of wind that is typical random process with Dryden turbulence spectrum. The proposed geometrical structure of radar system is composed of one transmitter and multiple receivers. To achieve high accuracy of locating a stealth target, the proposed scheme uses accuracy RCS measurement to compute Stealth target position. Simulations demonstrate that proposed scheme using one transmitter and multiple balloon-borne receivers give much higher location accuracy comparing to other geometrical systems because of increasing the PO – scattered field with higher aspect angles.

The theory of fractional order calculus is applied to construct variations of the fundamental Pareto clutter model density, used in X-band maritime surveillance radar. Such data are characterised, at high resolution, by spiky clutter returns whose density function possesses heavy tails. By an application of fractional calculus to the Pareto distribution function, together with optimisation applied to determine the fractional derivative order, it is possible to obtain a new model for radar clutter. This is shown to fit real radar clutter returns better than a standard Pareto model. Additionally, it accounts for receiver thermal noise without the complexity of an additional noise distribution.

Owing to the vulnerability of synthetic aperture radar (SAR) system to interferences, effective interference suppression has been an urgent task for SAR imaging. In this work, a novel time-varying narrowband interference and wideband interference suppression method is presented based on time-frequency reconstruction and mask technique. This method consists of four key stages. First, the authors present an efficient signal reconstruction method (ESRM) based on eigenvalue decomposition from the Wigner distribution. Next, echoes contaminated by the interference are identified in the frequency domain and the jamming components are obtained by using the mask technique in time-frequency plane. Then, the ESRM is applied to quickly and accurately synthesise interference signals by incorporating the principle of energy minimum without the need of the prior knowledge of the interference. Finally, the interference components are subtracted from the echoes in data domain, and the well-focused SAR image is obtained by conventional imaging algorithm. Results of simulated and measured data prove the validity of the proposed method.

Weak target detection based on fractal analysis is a hot research topic. The existing methods, using single fractal dimension and Hurst exponent, are not applicable under low signal clutter ratio (SCR) conditions. This study focuses on enhancing the performance of weak target detection by utilising the multifractal properties of sea clutter. The existing global multifractal spectrum based method has limited performance because of its non-stability. Therefore this study proposes a weak target detection method by taking into account the local difference of multifractal spectrum between sea clutter with and without target. The local-multifractal spectrum is obtained by adding a rectangle window to the multifractal spectrum, and the local difference is calculated by the local mean square summation algorithm. In addition, the window length, a key parameter for obtaining the local-multifractal spectrum, is adaptively computed by the slope of the singularity intensity. In comparison with the existing multifractal spectrum based method, the experimental results of real S-band and X-band sea clutter data show that the proposed method is more stable, and could achieve a better detection performance under low SCR conditions.

The efficient scan moving target indication (MTI) mode is implemented in the wide-area ground MTI systems for the purpose of wide-area surveillance. However, because of the scanning movement of the radar antenna, it is difficult to acquire enough coherent pulses in a single azimuth direction in the Doppler beam sharpening (DBS), so the sharpening ratio is greatly limited. To mitigate this problem, a combined super-resolution algorithm with aperture extrapolation for DBS imaging is proposed to enhance the sharpening ratio in this study. In this algorithm, aperture extrapolation technique is utilised to increase the data length in azimuth direction and the amplitude and phase estimation of a sinusoid, which can acquire accurate spectral estimation with much lower side lobes and narrower spectral peaks, is applied to replace the fast Fourier transform to perform the Doppler analysis. In this way, the sharpening ratio in the new algorithm could be enhanced by one time. Experimental results on simulation data and real data verify the effectiveness of the new super-resolution algorithm, and demonstrate that the proposed algorithm can provide sharp and clear scene information with lower side lobes and narrower peaks.

Power minimisation approach is an effective interference suppression algorithm for satellite navigation systems. It forms automatically deep nulls in the direction-of-arrival (DOA) of interferences without prior information about the DOAs of satellite signals and interferences. However, it cannot provide flat gains for other directions. Thus, the desired satellite signals may be partly suppressed when they locate in the shallow nulls. By combining eigenvalue thresholding method and l1-norm constraint, a new interference suppression algorithm is proposed for satellite navigation systems that would provide approximately flat gains in all directions except that of interferences. However, the l1-norm constraint leads to a non-smooth optimisation problem which cannot be solved by the conventional gradient-based algorithm. After that, by utilising the proximal operator, an iterative algorithm is proposed. The simulations demonstrate the effectiveness of the proposed algorithm.

Classification of different human activities using multistatic micro-Doppler data and features is considered in this study, focusing on the distinction between unarmed and potentially armed personnel. A database of real radar data with more than 550 recordings from 7 different human subjects has been collected in a series of experiments in the field with a multistatic radar system. Four key features were extracted from the micro-Doppler signature after a short time Fourier transform analysis. The resulting feature vectors were then used as individual, pairs, triplets and all together before inputting to different types of classifiers based on the discriminant analysis method. The performance of different classifiers and different feature combinations is discussed aiming at identifying the most appropriate features for the unarmed against armed personnel classification, as well as the benefit of combining multistatic data rather than using monostatic data only.

This study addresses the narrowband signal detection with unknown frequency, direction of arrival, complex amplitude and noise variance. The authors find a separating function (SF) using the maximal invariant of induced group of transformations. Then three separating function estimation tests (SFETs) are proposed which called SFET₁, SFET₂ and SFET₃. It is shown that the SFET₁ using the maximum likelihood estimation (MLE) of SF is equal to the generalised likelihood ratio test. The SFET₂ and SFET₃ are proposed to reduce the computational complexity of SFET₁, based on a proposed estimation named by averaged MLE. The authors show that the proposed tests are constant false alarm rate. Moreover it is shown that the proposed tests are asymptotically optimal by increasing the number of snapshots and antennas. The simulation results show that the SFET₃ outperforms the SFET₁ and SFET₂ and the decreasing rate of miss detection against the number of snapshots for SFET₃ is higher than that for SFET₁ and SFET₂.

The back-projection algorithm (BPA) is a useful technique for synthetic aperture radar (SAR) imaging. The fast factorised BPA (FFBPA) recursively partitions the back-projection integral, thus significantly reducing the overall computation complexity corresponding to the improvement obtained by the FFT algorithm compared with the direct implementation of the discrete Fourier transform. In this study, the authors propose a new fast method, termed as the factorised polar-format BPA (FPFBPA), which combines the polar format algorithm and the factorised back-projection concept. It is demonstrated that, when the first-stage subaperture in the FPFBPA contains more than 3 pulses, the proposed method further reduces the computation complexity comparing with FFBPA, provided that the same interpolation method is used. The proposed algorithm is also capable of processing curved orbit and multi-mode SAR data. The effectiveness of the proposed algorithm is verified by the processed results using measured airborne data.

This study presents a two-step least-squares approach for estimating the position and velocity of a moving emitter using time difference of arrival (TDOA) and frequency-difference of arrival (FDOA) measurements in a two-dimensional scenario. The proposed method first estimates the emitter position based on the asymptotes of TDOA hyperbolae and then linearises the non-linear equations of FDOAs using the estimate of the emitter position obtained in the first stage. Although the proposed method has lower performance than other methods in terms of estimation accuracy, it provides a closed-form solution without geometric constraints of sensor placement and an initial guess of emitter parameters. Since many methods derive the estimates of position and velocity with iterative numerical techniques, the proposed method can be a good alternative to set the initial guess under conditions of low measurement error. Simulation results are included to validate the algorithm, and its performance is compared with the Cramer–Rao lower bound.

This study considers the design of optimal receive filter under similarity constraint in coloured noise and compares it with signal design methods and conventional schemes. Similarity constraint restricts the sought-after filter to be close to the transmit waveform to control the output sequence envelope, avoiding potential risks of poor range solution and high sidelobes of whitening filter (WF) in severe coloured noise. The detailed solution to this constrained optimisation problem is provided. Then, the authors compare the filter design (FD) with the schemes of conventional or designing signal based on the matched/whitening filter. Five schemes are analysed on their performances of output signal-to-noise ratio, sequence control and requirements for practical applications. The merits of five schemes are concluded. In simulations, comparison between the designed filter and whitening filter illustrates the necessity of similarity constraint. FD under similarity constraint is regarded as a robust scheme for output sequence envelope control, easy to implement for coloured noise suppression.

In airborne case, synthetic aperture radar images generally suffer from the deterioration because of the unknown phase error caused by unstable platform and atmosphere perturbation. To obtain the phase error, a novel autofocus algorithm referred to as blind homomorphic deconvolution autofocus algorithm is proposed in this study. In this method, a wavelet scaling function is used to construct a smooth subspace that is orthogonal to noise subspace. Then, the phase error can be separated and reconstructed by the generated smooth subspace based on the differences of the smoothness properties between phase error and image reflectivity. Compared with the traditional autofocus methods, the proposed method does not require an iterative estimation. Thus, the computational complexity can be significantly reduced. Simulation and real data processing results validate the effectiveness of the proposed method.

In global positioning system modernisation, a new civil signal namely L2C signal has been broadcast since 2005. Compared with the widely used C/A code signal, although the new signal provides lots of advantages such as better acquisition and tracking performances, the used civil moderate (CM) code and civil long code have much longer periods than C/A code and they make L2C signal acquisition challengeable. Although previous acquisition methods are effective, their computational complexities are still high. To this end, in the study, a composite CM (CCM) code structure is developed by reconstructing the previous return-to-zero CM (RZCM) code through the previous folding technique. Then the CCM code is comprehensively assessed. Compared with the RZCM code, the developed CCM code has following advantages. It can be implemented by small scale FFT block, which is desirable for resource-limited L2C receivers; it is more robust against navigation data and carrier Doppler, and performs more reliable detection performance; for normally received L2C signal, which is usually not <42 dBHz, it spends less time on acquisition. Theoretical and simulation results demonstrate the advantages.

Range/Doppler migrations, which result from the integration time increasing and the target's manoeuvring motion, will affect the coherent integration performance severely. To deal with range/Doppler migration, a novel coherent integration algorithm, improved axis rotation discrete chirp-Fourier transform (IAR-DCFT), is proposed. IAR-DCFT could eliminate range migration via improved axis rotation transform, and realise the compensation of Doppler migration and coherent integration via discrete chirp-Fourier transform. IAR-DCFT may be regarded as tri-dimensional motion parameter filter banks, which is analogous to moving target detection that can be treated as Doppler filter banks, and estimate a target's velocity, acceleration and jerk simultaneously. Then the derivations of maximum-likelihood estimator and likelihood ratio test detector show that IAR-DCFT is the optimal estimator and a detector. The performance of the optimal estimator is verified by comparing with Cramer-Rao lower bound. Subsequently, the detailed performance analyses of IAR-DCFT are provided, including coherent integration gain, coherent integration time, multi-target detection and computational complexity. Furthermore, the authors introduce the generalisation of IAR-DCFT, that is, multi-range-cell associated IAR-DCFT (MR-IAR-DCFT), which can be applied to detect a target with high-manoeuvring motion or used in a longer time integration case. Finally, some numerical experiments are given to verify the performance of IAR-DCFT and MR-IAR-DCFT.